Research Themes

The EPSRC-MRC SABS CDT is an innovative 4-year D.Phil. programme where every student works in collaboration with industry to develop novel computational, mathematical and physical techniques to solve biomedical research problems. Our students conduct their doctoral research within one of three broad research themes:

Computational and structural approaches underpinning drug and therapy discovery: Computational and structural approaches are an indispensable component of the modern drug discovery pipeline, shedding light on important factors such as mechanism of action, axis of therapeutic intervention, target selectivity and drug resistance. These approaches have been credited with the success of a number of new chemical entities and, more recently, have been increasingly utilised in the development of new biological entities, including monoclonal antibodies. Such approaches are uniquely positioned to synergise chemical and biological drug development processes.

Data-driven drug discovery: High-throughput technologies are having a marked impact on the pharmaceutical industry. The ability to perform routine genotyping or sequencing of host (human) genetics and their pathogens or tumours provides unique opportunities for patient stratification and improved personalisation of drug treatment. Moreover, many drugs fail late in development due to adverse reaction in a small population of patients. Coupled to high-throughput genetics, health institutes are increasingly moving toward the recording and storage of population electronic health records providing detailed longitudinal phenotyping of response to treatment and confounding environmental factors. The linking of population electronic patient records with high-throughput genetic and genomic biomarkers has the potential to transform drug stratification and is moving aspects of pharmaceutical research into the area of data-driven science.

Physiological modelling underpinning drug discovery: A key challenge in the development of novel drugs and therapies is obtaining a detailed understanding of how treatment interventions interact and affect the complex physiological processes that constitute living organisms. Addressing this central issue requires the development of biophysically consistent mathematical models which can be integrated with multiple types of functional data into a consistent [quantitative and predictive] theoretical framework. The resulting models typically describe multiple physical processes, often occurring across a range of spatial and temporal scales, and yielding solutions only via computational approaches.

SABS provides training and research across a wide range of areas, including the design and testing of new chemical and biological entities, modelling biological systems, and robust analysis of complex datasets. Such cross-disciplinary work will introduce students to cutting edge organic chemistry, chemoinformatics, chemical and synthetic biology, biophysics, advanced computational simulation, bioinformatics, data mining, statistical analysis, physical and structural study of biomolecules, and mathematical modelling.